by March 1, 2000 0 comments

Before we venture into how to manage knowledge, it’s
essential to have a clear understanding of what we mean by knowledge, so that we know what it is that we’re setting out to manage, and what falls outside the ambit of our knowledge management exercise.

At the very beginning is Data
Organizations have a large appetite for data. Almost every piezce of data that reaches an organization gets recorded by someone or the other in ledgers, account books, databases, spreadsheets…

This data essentially represents the past–sales performance of last year, rainfall data of the last 100 years, number of unique page views yesterday, and so on. You can obviously never have data for the future. The bulk of the data in your organization would consist of numbers. All this data by itself is useless, since it is difficult to make sense out of pure numbers. To make sense out of data, you need to organize the numbers properly, and compare them with other similar numbers.

From data comes Information
Data, when organized and interpreted, gives us information. Comparing the sales data of this month to that of last month will tell us whether we’re doing better this month. Comparing the rainfall data for past years can tell us about seasonal trends in rainfall, and so on.

Information is presented as cross tabulations, graphs, statistical coefficients, and so on. In organizations, information is usually stored in spreadsheets, presentations, etc.
Information, they say is power. But does having the information and sitting on it make you powerful? Not really. Information has to be acted upon, so that you can derive benefits.

Using information
How do you act on information? Typically, you would, using the past data and the information derived from it, attempt to predict the future. Is it likely to rain tomorrow? How many copies of 
PC Quest are likely to sell next month? 

This attempt at predicting the future doesn’t work in isolation.
On to the available information (patterns), you apply a number of other factors, such as your past experience, your gut feel, advice from “experts” based on their experience, etc. For example, suppose I’m trying to predict how many copies of PC Quest are likely to be sold in March 2000. Suppose that from the data available to me, I’ve derived the information that March is traditionally when sales peak. Now the question in my mind is, why do sales peak in March? Is it because people like to read more in March? Is it because we’ve had strong stories in March? Or is there some other factor at play? In short, what do I have to do that this year too, we do well, or even better than before, in March?

Knowledge in action
First, from past experience, I know that in March, we’ve had strong stories. I also know that March is the time when exams are over, and I hazard a guess that more school and college students will buy PC Quest in March. But is there anything else? To find out, I proceed to consult an expert on the subject–Harsh Chutani, our circulation manager. Harsh tells me that in March, sales in the metros fall, while they pick up in the other states, because families move from the metros back to their native places on holiday. He also tells me that we’ve traditionally run our stands publicity campaigns in March, thereby inviting the attention of new readers to the magazine.

Now, none of these insights are available in our databases or in our spreadsheets. They’re in the minds of the people concerned.

It is these insights that we term as knowledge.
So, like information is distilled out of data, past experiences, insights, and others’ expertise when applied to information gives us knowledge, and this helps us make better decisions for the future.

Managing knowledge
As you saw, knowledge about the reasons for the strong sales performance in March was not available readymade anywhere. Part of it was based on my previous experience, and my gut feel. For the rest, I had to go and seek it out from the concerned expert. As organizations grow in size and complexity, it may not be that easy to identify experts. Also, the expert may not always be available to provide his or her insight. He or she may be busy with something else, may be on leave, or may even have left the organization.

Does that mean that organizations have to forego maximum use of the knowledge residing in the expert?
It is in answer to this dilemma that knowledge management—or KM as it’s fondly known—came into being. KM basically deals with ways and means of capturing and making available knowledge of the experts to others, in electronic form. Knowledge Management systems also help you locate, contact, and communicate with experts (knowledgeable people) on various subjects, within your organization, or maybe even outside.

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